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Intelligent Approach for Data Collection in Wireless Sensor Networks

2011
Journal from gdlhub / 2017-08-14 11:52:32
Oleh : Yujin Lim, Sanggil Kang, IAJIT
Dibuat : 2012-06-23, dengan 1 file

Keyword : Coupled input, decoupled input, wireless sensor network, intelligent data collection
Subjek : Intelligent Approach for Data Collection in Wireless Sensor Networks
Url : http://www.ccis2k.org/iajit/PDF/vol.10,no.1/2797-11.pdf
Sumber pengambilan dokumen : internet

In wireless sensor networks, one of most important issues is data collection from sensors to sink. Many researchers


employ a mathematical formula to select the next forwarding node in the network-wide manner. We are motivated that


surrounding environments for nodes are different in time and space. Because different situations of nodes are not considered


for selecting the next forwarding node, the performance of data collection is degraded. In this paper, we present an intelligent


approach for data collection in sensor networks. We model a nonlinear cost function for determining the next forwarder


according to the input types whether inputs are correlated or uncorrelated for generating the output of the function. In our


method, the correlated inputs are presented in a weighted sum with the dependent fashion but the uncoupled inputs with an


independent fashion in the nonlinear function. The weights in the functions are determined to the direction in which the


reliability of data collection maximizes. In the experimental section, we show that our method outperforms other conventional


methods with respect to the efficiency in data collection from sensors to sink.

Deskripsi Alternatif :

In wireless sensor networks, one of most important issues is data collection from sensors to sink. Many researchers


employ a mathematical formula to select the next forwarding node in the network-wide manner. We are motivated that


surrounding environments for nodes are different in time and space. Because different situations of nodes are not considered


for selecting the next forwarding node, the performance of data collection is degraded. In this paper, we present an intelligent


approach for data collection in sensor networks. We model a nonlinear cost function for determining the next forwarder


according to the input types whether inputs are correlated or uncorrelated for generating the output of the function. In our


method, the correlated inputs are presented in a weighted sum with the dependent fashion but the uncoupled inputs with an


independent fashion in the nonlinear function. The weights in the functions are determined to the direction in which the


reliability of data collection maximizes. In the experimental section, we show that our method outperforms other conventional


methods with respect to the efficiency in data collection from sensors to sink.

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